AI for Ads: Dynamic pricing driving or curbing competition?

Competitiveness is having a field day, as global tech majors are coming under scrutiny and more importantly, sanctions, from more and more governments around the world – whether it’s Apple being fined in the EU or Meta in Australia for their product monopolies or Google battling the “most significant antitrust trial of the century” in the US. Closer home, Amazon and Walmart-backed Flipkart have been accused of anti-competition and predatory practices in India just last week. While the reasons for these industry-wide practices are complex and multi-fold, AI is, as elsewhere, becoming a major factor in them. While exchange4media has previously covered the impact of AI technologies on digital ad spends, the advertising industry’s wish list for AI regulations, AI and machine learning algorithms are revolutionizing dynamic pricing strategies in digital advertising and publishing. These technologies allow companies to analyse vast amounts of real-time data on factors like user behaviour, market demand, competitor pricing, and inventory levels to automatically adjust prices for ad space or content access.

Competitiveness is having a field day, as global tech majors are coming under scrutiny and more importantly, sanctions, from more and more governments around the world – whether it’s Apple being fined in the EU or Meta in Australia for their product monopolies or Google battling the “most significant antitrust trial of the century” in the US. Closer home, Amazon and Walmart-backed Flipkart have been accused of anti-competition and predatory practices in India just last week. While the reasons for these industry-wide practices are complex and multi-fold, AI is, as elsewhere, becoming a major factor in them. While exchange4media has previously covered the impact of AI technologies on digital ad spends, the advertising industry’s wish list for AI regulations, AI and machine learning algorithms are revolutionizing dynamic pricing strategies in digital advertising and publishing. These technologies allow companies to analyse vast amounts of real-time data on factors like user behaviour, market demand, competitor pricing, and inventory levels to automatically adjust prices for ad space or content access.

Hitesh Nahata, Director of Data Science & Analytics at MiQ, offers a nuanced perspective on the impact of AIpowered dynamic pricing, saying, “AI-powered dynamic pricing can lead to implicit price collusion, but this is more common in industries nearing market saturation. The dynamic and ever-evolving nature of the programmatic advertising industry has kept it from becoming a large-scale problem.”

Essentially, the mechanics of dynamic pricing are increasingly seeing AI algorithms continuously scan competitors' prices to adjust in real time. While this may seem like a win for users, research shows that as AI algorithms become more widespread, they may actually result in implicit price collusion. Nahata points out that the expanding supply side, with new channels like Connected TV, digital out-of-home, and audio, has led to more inventory availability than ever before. He adds, “As of now, there is no evidence suggesting that these algorithms follow uniform optimization rules, reducing the immediate risk of implicit price collusion in this space.”

However, Sanjeev Jasani, Group COO at Cheil SWA, expresses more concern about potential pricing issues, opining, “As AI gets better at changing prices quickly, we might see some unplanned teamwork between companies. I'd say there's a pretty good chance - like 7 or 8 out of 10 - that prices will start to look very similar. It's not that companies are trying to work together, but when everyone uses similar tech, prices can end up matching.”

For advertisers, AI-powered systems can optimize bid prices for ad placements across platforms, maximizing ROI by finding the ideal balance between cost and performance. Publishers use similar AI tools to set optimal prices for their ad inventory, potentially increasing revenue by charging higher rates during peak demand periods or for high-value audience segments. Gulab Patil, Founder & CEO of Lemma, sees this as a positive development, saying, “Automation in real-time price detection and bid optimization is a paradigm shift for bidding algorithms. In fact, this is a Machine Learning (ML) system at this moment, but SSPs and DSPs are building predictive AIs to determine the true price and assist both supply and demand in determining the true value.” Patil believes that AI will contribute to accurate pricing and bring transparency to the advertising industry, potentially addressing issues of under or overselling media. However, the increased efficiency brought by AI-driven pricing is creating a more competitive marketplace, where success increasingly depends on having sophisticated algorithms and data analysis capabilities. This shift raises concerns about potential negative impacts on the industry.

Abhishek Upadhya, SVP of Digital Innovation & Strategy at HiveMinds, emphasizes the need for AI watchdogs to prevent unchecked price rises and suggests using collusion detection and price-correlation algorithms to flag problematic situations. “In case any price increases become unviable, platforms will get voted out of the media plans - however opaqueness in the pricing practices is definitely causing an issue in doing a fair assessment of these AI-based platforms,” he says. To address these challenges, experts propose various strategies. Nahata recommends “focusing on efficiency through better targeting and personalisation, optimizing for long-term goals like customer lifetime value, diversifying ad inventory across newer channels, leveraging supply path optimization (SPO) to reduce middlemen, and setting bid caps and budget controls.” Jasani advises companies to differentiate themselves beyond price. “Put money into making customers happy and providing a great product experience across touch points, and implement long-term reward programs to drive loyalty.”

Saurabh Gupta, CEO and Founder of VeriSmart AI, suggests a shift in focus, saying, “While AI has excelled at automating content generation, we must now shift our attention to discovering better audiences. By using generative AI prompts to query intelligent data sources in real time, we can identify the right audience groups.” As the industry continues to grapple with the implications of AI-driven dynamic pricing, it's clear that both opportunities and challenges lie ahead. Balancing the benefits of increased efficiency and accuracy with the need for fair competition and transparency will be crucial in shaping the future of digital advertising and publishing.